King's College London

Research portal

Simulation ready anatomy model generation pipeline for virtual surgery

Research output: Contribution to journalArticlepeer-review

Kun Qian, Meili Wang, Yaqing Cui

Original languageEnglish
Article numbere1986
JournalComputer Animation and Virtual Worlds
Issue number6
Published1 Nov 2021

Bibliographical note

Funding Information: information Key Research and Development Program of Shaanxi Province, 2018NY-127; Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, China, 2018AIOT-09 Publisher Copyright: © 2021 John Wiley & Sons, Ltd.

King's Authors


For surgery simulation application, a high-quality anatomical model is very important not only for rendering but also for physics simulation. CT and MRI reconstructed model has no surface parameterization attribute so texture-based materials cannot be applied for rendering. Anatomical models on the digital market are efficient options but most can only be used for visualization because of the nonmanifold geometric degeneracies. We proposed a simulation ready model generation pipeline that can convert a nonmanifold polygonal surface mesh into a degeneracy free surface mesh (simulation ready state) while preserving the original model's surface parameterization attribute. Our pipeline includes two stages. The first stage is a voxelization and remesh based simulation ready model generation pipeline, which can keep the shape of the original three-dimensional surface model meanwhile eliminate the nonmanifold geometry. The second stage is the main contribution of this article. A cutting-based surface mesh parameterization transfer algorithm is proposed which can transfer the original surface parameterization (UV mapping especially the UV seam) to the simulation ready model. A detailed comparison with existing pipelines is made to show that our pipeline can achieve surface parameterization preservation feature and is more suitable for improving the efficiency of virtual surgery production.

View graph of relations

© 2020 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454